Welcome!
Nano-scale transistors fill warehouse-scale supercomputers, yet their performance still constrains development of the jets that defend us, the medical therapies our lives depend upon, and the renewable energy sources that will power our generation into the next. The Computational Physics Group at Georgia Tech develops computational models and numerical methods to push these applications forward. We accompany our methods with algorithms crafted to make efficient use of the latest exascale machines and computer architectures, including AMD GPUs, Arm/RISC CPUs, and quantum computers. We develop open-source software for these methods that scales to the world’s largest supercomputers. Check out the rest of this website to learn more.
Openings? Visit this page if you’re interested in joining our group.
Examples of our work
Bubble cavitation and droplet shedding are fundamental multiphase flow problems at the core of naval hydrodynamics, aerospace propulsion, and more. We developed a sub-grid method for simulating these phenomena. MFC, our open-source exascale-capable multi-phase flow solver, demonstrates such scale-resolving simulation of a shock-droplet interaction in the above video (via Ph.D. student Ben Wilfong).
The spectral boundary integral method leads to high-fidelity prediction and analysis of blood cells transitioning to chaos in a microfluidic device. This method of simulation provides resolution of strong cell membrane deformation with scant computational resources. We developed a stochastic model for the cell-scale flow, enabling microfluidic device design and improving treatment outcomes. The video above shows a microaneurysm (simulated by Suzan Manasreh).
News
28 November, 2024 Our paper on quantum solves of the Navier-Stokes equations using current quantum devices was accepted to Comptuters & Fluids! Congrats to Ph.D. student Jack Song and our collaborators at GTRI! You can view the current version on arXiv.
24 November, 2024 Our group is at APS DFD this week. Say hi and consider checking out some of our talks on multiphase flow, FSI, particle-laden flow, material characterization, and more! (most easily found via here and searching Bryngelson.)
16 November, 2024 Spencer is speaking at ART@SC24 today on HPC for PDE solves and large-scale training.
14 November, 2024 Our project ExaMFlow, based on MFC, is participating in JUREAP, the JUPITER Research and Early Access Program. ExaMFlow received the JUREAP certificate for scaling efficiency and node performance, with potential to use a significant part of the JUPITER Booster system and the first European exascale supercomputer, starting January 2025.
13 November, 2024 We will be at SC24 here in Atlanta next week. Our work includes cell-resolved simulations of aneurysms and exascale compressible flow methods. More here and here.
10 October, 2024 The group is awarded ACCESS-CI Accelerate annual allocation of 3M credits (equivalent to 45K A100 GPU hours) for developing sub-grid physics models!
20 September, 2024 Our work on a fully quantum lattice algorithm for solving the Navier-Stokes equations was recently published in AVS Quantum Science. Congrats to Sriharsha and Jack! We appreciate the collaboration with Bryan Gard (GTRI), Eugene Dumitrescu (ORNL), and Alex Alexeev (GT ME).
19 September, 2024 New paper on the use of the adjoint to compute averaged closure operators in turbulent flow was published in Physical Review Fluids! In collaboration with Jessie Liu and Ali Mani (Stanford), Florian Schäfer (GT), and Tamer Zaki (Hopkins).
18 September, 2024 Our Supercomputing (SC) paper from the WACCPD workshop was accepted. It is now on arXiv. We show how to achieve performant compute kernels on AMD GPU devices via OpenACC offloading, and use them to scale to all of OLCF Frontier. Congrats to Ben, Anand, and Henry! and thanks to our collaborators, Steve Abbot at HPE/Cray and Reuben Budiardja at Oak Ridge!
17 September, 2024 Our preprint, Rational-WENO, appears on arXiv. We construct a scheme that achieves near 5th order accuracy from a three-point stencil. In collaboration with Google Research and TU Munich.
